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Comparative Effectiveness Research : Rethinking Therapeutic Evaluation in Chronic Diseases

Comparative Effectiveness Research : Rethinking Therapeutic Evaluation in Chronic Diseases. Ph Ravaud. Therapeutic Evaluation of Chronic diseases. Today : mainly RCts and Meta-Analysis (one drug ) Tomorrow RCTs

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Comparative Effectiveness Research : Rethinking Therapeutic Evaluation in Chronic Diseases

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  1. Comparative EffectivenessResearch :RethinkingTherapeutic Evaluation in ChronicDiseases Ph Ravaud

  2. Therapeutic Evaluation of Chronicdiseases • Today : mainly RCts and Meta-Analysis (one drug ) • Tomorrow • RCTs • Meta-analysis and Network Meta-analysis (all drugs for a specific disease) • Observational Data

  3. TheClinical Trials System is broken • Too slow • Too expensive • Doesn’t answer many critical questions ( or doesn’t answer questions relevant for physicians • ( Short term , inadequate comparator, side effects) • Otherwise its great ( RCTs are the best way to obtain groups of patients comparable for known and unknown prognostic factors )

  4. Applicability or generalizability of trials • Patients included are not representative of the patients treated in usual care (trial patients are younger and with less co-morbidities) • Setting is not representative (centers are highly selected) • Treatments are evaluated mainly according to the principle “one size fits all”

  5. CriticalKnowledge Gaps • The paradox - 18,000 RCTs published each year - more than 350,000 RCTs available • Despite that available evidence remains limited or of poor quality

  6. Much of Care Today is Not Based on Scientific Evidence Less than 20% of AHA/ACC heart disease management recommendations are based on a high level of evidence and over 40% are based on the lowest level of evidence AND proportion of recommendations with high evidence levels has not increased over time Robert Califf, IOM Meeting on Evidence-based Medicine, December 2007

  7. From Meta-analysis to Network Meta-analysis All treatments available for a disease One treatment Less than 50/y Thousands/y

  8. Intervention D Network meta-analysis Intervention A Intervention C Intervention B Intervention E Intervention F Combining direct and indirect evidence

  9. BiologicTreatment in RheumatoidArthritis: Ongoing Trials • Only 5 head to Head trials • Ongoing Trials recruiting patients failing to respond to Methotrexate and with high disease activity

  10. Cost of RCTs: an example • 18,000 patients • Total crf pages 1.8 millions • Total crf variables 2.5 Billions • Total number of queries 600,000 • Cost 700 millions Euros • Treatment effects decrease over time , number of patients required mecanically increase

  11. Unrealistic to expect head-to-head RCTs addressing all 2-by-2 comparisons

  12. As much as we all love randomized effectiveness trials • It is an unrealistic expectation that we will have randomized trials for every intervention and its combinations in every patient subgroup ( for example if for a diseasewe have 20 differenttreatment options and 3 differentsubgroups of patients, weneedtheoriticallyat least 470 head to head trials !) • We need Effectiveness evidence in a timely manner. Randomized trials take time to conduct • Therefore, 85% of the CER evidence is from non-experimental data!* * Academy Health Report June 2009

  13. Transparency of clinical trials • Reporting guidelines • Clinicaltrial.gov 2005 • FDA amendment act 2007

  14. Consort Extensions • Too many extensions • Too many reporting guidelines • Editors do not really implement the guidelines • Quality of reporting remains poor

  15. Trial registration mandatorysince 2005( International Committee of Medical Journal Editors)

  16. Impact of dissemination bias Separate meta-analyses of the FDA and journal data sets show that the increase in effect size ranged from 11 to 69% for individual drugs and was 32% overall Turner et al. NEJM 2008 16

  17. SelectiveDisseminationBias

  18. FDA Amendment Act • US Federal law enacted in 2007 mandates registration and results reporting for clinical trials of drugs , biological products and devices at clinicaltrial.gov • Study sponsors or PI are requires to report summary results information within 1 year of completing data collection for teh prespecified primary outcome

  19. Levels of “Transparency” 21 Zarin DA, Tse T.. Science. 2008 Mar 7;319(5868):1340-2.

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